Physician Practices in the Management of Myocardial Injury after Non-Cardiac Surgery: A Survey Study
Bibliographic record
Abstract
Objective: To describe how physicians manage patients with myocardial injury (i.e., a troponin elevation of presumed ischemic origin) after non-cardiac surgery (MINS). Methods: Web-based survey to physicians distributed between December 2020 and September 2021, including a case scenario of asymptomatic MINS. Results: Of 103 respondents, 94% were practicing in Canada and 65% were general internists. 97% of respondents would order an ECG; following a normal ECG, 46% of would order an echocardiogram; following a normal echocardiogram, 42% would order myocardial perfusion imaging. Of the respondents, 91% and 90% would initiate ASA and a statin, respectively; 24%, 21%, and 7% would initiate an ACE inhibitor, a beta-blocker, and dabigatran, respectively. Most participants indicated that outpatient follow-up with a medicine specialist within 1–2 months (90%) and 1 year (68%) was appropriate. Conclusion: Respondents generally agreed that ASA and statins should be prescribed for MINS, and that post-discharge specialist follow-up is warranted. However, opinions regarding the role of cardiac imaging varied.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".